Analyzing Real Estate Data Problems Using the Gibbs Sampler

Real estate data are often characterized by data irregularities: missing data, censoring or truncation, measurement error, etc. Practitioners often discard missing- or censored-data cases and ignore measurement error. We argue here that an attractive remedy for these irregularity problems is simulation-based model fitting using the Gibbs sampler. The style of the paper is primarily pedagogic, employing a simple illustration to convey the essential ideas, unobscured by implementation complications. Focusing on the missing-data problem, we show dramatic improvement in inference by retaining rather than deleting cases of partially observed data. We also detail Gibbs-sampler usage for other data problems.     

Spatial Statistics and Real Estate

Real estate has historically employed statistical tools designed for independent observations while simultaneously noting the violation of these assumptions in the form of clustering of same sign residuals by neighborhood, along roads, and near facilities such as airports. Spatial statistics takes these dependencies into account to provide more realistic inference (OLS has biased standard errors), better prediction, and more efficient parameter estimation. This article provides an overview of the field and directs readers to the relevant literature and software.     

FINANCING AND HOUSE PRICES

Recent empirical evidence on the effect of below-market financing on house prices has suffered from estimation and interpretation problems. In this paper, a methodology is developed to solve these problems. Using data for mortgage revenue bonds, the methodology is tested with results indicating that all financing subsidy is capitalized into house prices.     

Selling price,financing premiums,and days on the market

Home buyers face the task of trading off selling price and the time required to sell a property. One factor that may affect this decision is the presence of financing premiums. The effects of financing premiums on the time a single-family home remains on the market is examined in this paper. The question is to what extent home sellers are willing to compromise on financing premiums and make concessions to buyers in order to sell their properties more quickly.The study uses a sample of single-family residential homes sold with assumption financing and new conventional financing. The sample covers segments of time when interest rates were relatively low and stable (1975–1976) and when rates were much higher on average and more volatile (1980).The results show that financing premiums were present in selling prices of assumption-financed home sales during the 1975–1976 period and that sellers were able to capture a premium and maintain the same average time on the market as properties with other types of financing. During a period of unfavorable market conditions, such as 1980, the results indicate that home sellers with assumption financing conceded or negotiated away any premium in order to significantly decrease the number of days their properties stayed on the market for sale.     

Government Supply of Land in a Dual Market

A dual land market is one in which the government owns a significant portion of developable land while real estate development is done primarily by the private sector. This article examines Singapore's experience with its system of government land supply in a dual market, focusing on its response to market signals as well as the interaction with the significant private supply of land. The example is relevant to the general problem of government sales of valuable assets. The private supply of developable land behaves in line with expectations. The government response to price signals differs only modestly from that of private landowners.     

PRICING FAST-PAY MORTGAGES: SOME SIMULATION RESULTS

The mortgage market has undergone rapid change in recent years, particularly in the introduction of alternative mortgage instruments. This paper explores one such instrument, the fast-pay (early equity) mortgage. Specifically, in this paper the focus is on how this type of mortgage would be priced relative to the standard conventional mortgage using historical yield data.     

Introduction to Special Issue on the Economics of Information in Real Estate Markets

The articles featured in this issue are introduced, their relationships noted, and their key points highlighted.     

A Complete Nonparametric Event Study Approach

Event studies have been used to examine the direction, magnitude, and speed of security price reactions to various phenomenon. Concerns over the lack of normality in stock return distributions motivated the introduction of nonparametric test statistics in the event study literature. A parametric procedure (OLS), however, has been extensively employed in the estimation of parameters for the market model. This paper, in contrast, applies Theil's nonparametric regression in the estimation of abnormal returns; an approach which is distribution free and provides a complete nonparametric approach for the detection of abnormal performance. Simulation results indicate Theil's estimation procedure offers a slight improvement in power in the detection of abnormal performance over the traditionally employed methodology. The results suggest employing Theil's nonparametric estimation procedure combined with the rank statistic. This complete nonparametric combination offers similar power with fewer underlying assumptions.     

Housing Vouchers,Tenant Quality,and Apartment Values

Landlords face unique concerns in maximizing profits when they accept subsidized as well as unsubsidized tenants. Subsidized tenants come with lower rental collection risk because part or all of the rent is paid by a public agency and accepting subsidized tenants may widen the potential tenant market. But subsidized tenants tend to reduce overall tenant quality and to impose higher operating costs. By accepting subsidies, landlords may also subject themselves to periodic site inspections that may increase capital costs. Further, subsidized tenants may eventually crowd out unsubsidized tenants, lowering the average quality of the resident mix. Tests from Washington, DC apartments on accepting and advertising for Section 8 tenants support these qualitative predictions. Accepting Section 8 tenants enhances revenues, but advertising for them lowers revenues. More aggressive solicitation of subsidized tenants leads to a crowding out or displacement risk that dominates over any diminished collection risk.     

The Long-Run Performance of REIT Stock Repurchases

This study investigates the long-horizon performance of open-market stock repurchases for real estate investment trusts (REITs). We develop a new methodology to model the autocorrelation of monthly returns into long-horizon buy-and-hold abnormal return estimators. Serial correlation can introduce bias (autocorrelation bias) because the bid-ask bounce may affect monthly returns for sample firms and non-sample firms in a different fashion. Previous long-horizon event studies have overlooked this source of bias. There is compelling evidence that the market underreacts to the stock repurchase announcements. The evidence holds for different measures of the variance and the effects of cross-correlation of abnormal returns. Results are also robust to the traditional buy-and-hold abnormal return and the wealth relative estimators. We investigate the nature of the underreaction and find strong support for the undervaluation hypothesis.